Date of Graduation


Document Type


Degree Name

Master of Science in Geography (MS)

Degree Level





Jackson Cothren

Committee Member

W. Fred Limp

Second Committee Member

Marty Matlock

Third Committee Member

Kusum Naithani


Conservation delivery, Landscape ecology, Land use land cover change, Monarch butterfly, Resource planning


Over the past 20 years notable decreases in monarch butterfly populations have led researchers to begin evaluating the landscape for changes and seeking out opportunities for enacting conservation programs to better support their survival. The monarch butterfly has recently come under consideration for listing under the Endangered Species Act which has created a need for a more informed view of the landscape through which the migrate and breed, the central United States. In this research three spatially-explicit models are explored using the most applicable datasets currently available to address pressing policy and land manager decisions regarding monarch butterfly and pollinator conservation. Using the Cropland Data Layer (CDL) and National Land Cover Data (NLCD) datasets, individually and combined, the ability to to evaluate landscape change, annual and decadal, from 2008 – 2017 is evaluated. The CDL and NLCD both present unique data integration challenges for reliably estimating land use change on an annual basis for all land cover types, and for augmenting additional feature data, such as soil productivity and transportation networks that represent valuable target areas for monarch and pollinator research. The result of these spatially-explicit model trials are a more informed process for quantifying uncertainty and moving toward thoughtful inclusion of CDL data in annual change metrics that identifies land conversion for a broad number of categories, including grassland/pasture. The results of these models begin to identify a more consistent and transferrable process for addressing policy and land manager decisions regarding monarch butterfly and pollinator conservation delivery.